Color Theme Tag Descriptiveness Estimation
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Solution Overview
Problem
Existing color theme searching systems face inefficiencies due to inconsistent and irrelevant tagging, making it time-consuming for users to find and organize color themes, especially in large collections.
Innovation Solution
A method to estimate the descriptiveness value of tags based on weighted color attributes, which are determined by their associations and absence in a color theme collection, allowing for improved searching and suggesting of tags for color themes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual browsing is used to find color themes in large collections, then users can explore available themes, but the process becomes time-consuming
Solution Approach 1:
The system pre-computes color attributes and descriptiveness values for all color themes in the collection before search requests arrive. This preliminary processing creates an organized structure of color characteristics that enables rapid retrieval during actual search operations, eliminating the need for time-consuming manual browsing or real-time analysis.
Solution Approach 2:
The patent replaces manual browsing with an automated computerized search system that uses algorithms to compute color attributes, determine descriptiveness values, and retrieve matching themes. This substitution of mechanical/manual processes with automated computational methods dramatically reduces search time while maintaining ease of operation.
2Ease of operation
If tags are used to organize color themes, then finding and organizing themes becomes easier, but inconsistent and irrelevant tagging reduces search effectiveness
Solution Approach 1:
The system computes descriptiveness values by analyzing the relationship between tags and color attributes across the entire collection. This feedback mechanism evaluates how well each tag describes color themes based on actual color data, allowing the system to identify and correct inconsistent or irrelevant tagging. The descriptiveness metrics provide quantitative feedback on tag quality.
Solution Approach 2:
The patent transforms subjective tag quality assessment into an objective parameter by computing descriptiveness values based on color attributes. This parameter change from qualitative judgment to quantitative measurement allows for consistent, reliable evaluation of tag effectiveness and enables automated optimization of tagging consistency across the collection.
3Measurement precision
If exact tag matching is used for searching, then precise results are obtained for exact tags, but searches fail to find relevant themes with similar but not exact tags
Solution Approach 1:
The system adds a new dimension to search by computing descriptiveness values that measure the degree of match between search tags and color theme attributes. Instead of binary exact matching, this dimensional approach allows searches to evaluate multiple levels of relevance, enabling both precise exact matches and flexible similar matches within a unified framework.
Solution Approach 2:
The search system transitions from static exact matching to dynamic similarity-based matching using descriptiveness values. The system can adapt its search criteria based on the computed descriptiveness metrics, allowing users to find both exact matches and thematically similar color themes, thereby providing both precision and flexibility in search results.
Data Source
AI summary
Embodiments of the present disclosure assess how well a tag describes a color theme by estimating a descriptiveness value for the tag for the color theme. Some embodiments determine descriptiveness values for a tag based on weighted color attributes determined from the tag's existing use in a color theme collection. Descriptiveness values are used generally in color theme searching and to suggest tags for a color theme, among other things.